本研究探討Sentinel-1偵測數值地形圖異動區的能力，以2015年、2019、2020年與2021年Sentinel-1大台北地區作為實驗區，產製差異影像進行變遷偵測，並以Sentinel-2、Google街景與新北市1/1000數值地形圖修測成果作為驗證資料，確認Sentinel-1具備變遷偵測能力，並採用3個指標:分類準確度、精密度、kappa係數來量化變遷偵測的成果。
地形圖修測作業中位置資訊是重要因子，實驗中量測地理對位後Sentinel-1影像中10個控制點TWD97坐標，並與農航所提供的正射影像中同名點坐標進行比較，得到平均較差為13.9公尺，以Sentinel-1地元尺寸換算，相當於1像元左右的誤差。另外模擬在無DEM輔助地理對位的情況下，嘗試以仿射轉換配合10個控制點進行地理對位，整體精度最高可達±7.6公尺(約0.58個像元)。
透過兩時期雷達影像相減所計算的差異影像是本研究用作變遷偵測的方式設定不同門檻值於差異影像，歸納得到差異影像中設定以分貝差8以上 (|∆dB|>8)為門檻，能有好的異動區分辨能力，進一步地提出人造建物雷達強度作為附加判斷條件，試圖從變遷區域中分辨人造建物。
最後，Sentinel-1雷達影像偵測的異動區域與新北市數值地形圖中永久房屋異動區套疊，在無附加條件與有附加條件下，分別得到79.8%與90.7%的總體準確率；正確判別永久性房屋異動的精密度分別為10.0%與8.5%；kappa係數分別為0.057和0.026。整體研究成果得到Sentinel-1雷達差異影像存在大面積異動區的偵測能力，可作為異動區偵測的補充資料，但對於小區域及微小的變化仍容易誤判。

The capability of using Sentinel-1 at finding the topographic data change part is discussed in this thesis. Fore sentinel-1 images sensed at 2015, 2019, 2020 and 2021 are chosen as experimental data. Sentinel-2, Google street map and digital topographic map are used as reference data to validate the correctness of change detection.
Because the correctness of location is an important factor when finding the change area, 10 control points measured from Sentinel-1 image are compared with the corresponding points in orthophoto to evaluate the precision. The average difference is 13.9 meters. In addition, the simulation of terrain correction without DEM is also discussed. Affine transform is applied with same control points to simulate terrain correction. The best overall precision can reach ±7.6 meters(about 0.58 pixel).
Difference image calculated by two SAR image subtraction is the way to detect the change area in this study. By testing several thresholds, the result concludes that the threshold which set bigger than 8 decibel provides good distinction to classify change and non-change part. Moreover, the additional condition based on radar intensity is also demonstrated to improve buildings from change detection.
At the end, Sentinel-1 change area overlays with the digital topographic map to analyze the detection of permanent buildings change. Calculate the overlapping area of change detection result and digitalized ground truth. Without additional condition, the overall accuracy of change detection is 79.8%. The precision is 8.5%, and kappa coefficient is 0.026. With additional condition, the overall accuracy of change detection reaches 90.7%. The precision is 10.0%, and kappa coefficient is 0.057. This research shows that Sentinel-1 can be used to detect the big change area in digital topographic map, but the small change area and the detail cannot be found.

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